<!DOCTYPE HTML>
<html lang="en" >
    
    <head>
        
        <meta charset="UTF-8">
        <meta http-equiv="X-UA-Compatible" content="IE=edge" />
        <title>Python可视化 | Python 数据分析学习目录</title>
        <meta content="text/html; charset=utf-8" http-equiv="Content-Type">
        <meta name="description" content="">
        <meta name="generator" content="GitBook 2.6.7">
        
        
        <meta name="HandheldFriendly" content="true"/>
        <meta name="viewport" content="width=device-width, initial-scale=1, user-scalable=no">
        <meta name="apple-mobile-web-app-capable" content="yes">
        <meta name="apple-mobile-web-app-status-bar-style" content="black">
        <link rel="apple-touch-icon-precomposed" sizes="152x152" href="../gitbook/images/apple-touch-icon-precomposed-152.png">
        <link rel="shortcut icon" href="../gitbook/images/favicon.ico" type="image/x-icon">
        
    <link rel="stylesheet" href="../gitbook/style.css">
    
        
        <link rel="stylesheet" href="../gitbook/plugins/gitbook-plugin-highlight/website.css">
        
    
        
        <link rel="stylesheet" href="../gitbook/plugins/gitbook-plugin-search/search.css">
        
    
        
        <link rel="stylesheet" href="../gitbook/plugins/gitbook-plugin-fontsettings/website.css">
        
    
    

        
    
    
    <link rel="next" href="../Python可视化/绘图库-Matplotlib/Matplotlib常见图表.html" />
    
    
    <link rel="prev" href="../数据分析库的操作/13.1透视表和交叉表.html" />
    

        
    </head>
    <body>
        
        
    <div class="book"
        data-level="5"
        data-chapter-title="Python可视化"
        data-filepath="Python可视化/绘图库-Matplotlib.md"
        data-basepath=".."
        data-revision="Wed Oct 24 2018 21:30:49 GMT+0800 (中国标准时间)"
        data-innerlanguage="">
    

<div class="book-summary">
    <nav role="navigation">
        <ul class="summary">
            
            
            
            

            

            
    
        <li class="chapter " data-level="0" data-path="index.html">
            
                
                    <a href="../index.html">
                
                        <i class="fa fa-check"></i>
                        
                        数据分析
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="1" data-path="Python数据分析序言/内容序言.html">
            
                
                    <a href="../Python数据分析序言/内容序言.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>1.</b>
                        
                        Python数据分析内容
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="2" data-path="python数据分析环境和工具/Python数据分析相关.html">
            
                
                    <a href="../python数据分析环境和工具/Python数据分析相关.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>2.</b>
                        
                        python数据分析环境和工具
                    </a>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="2.1" data-path="python数据分析环境和工具/1Python数据课程软件和环境安装.html">
            
                
                    <a href="../python数据分析环境和工具/1Python数据课程软件和环境安装.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>2.1.</b>
                        
                        Python数据课程 软件和环境安装
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="2.2" data-path="python数据分析环境和工具/2python发行版.html">
            
                
                    <a href="../python数据分析环境和工具/2python发行版.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>2.2.</b>
                        
                        python发行版
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="2.3" data-path="python数据分析环境和工具/5交互式编辑器-JupyterNotebook.html">
            
                
                    <a href="../python数据分析环境和工具/5交互式编辑器-JupyterNotebook.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>2.3.</b>
                        
                        交互式编辑器-JupyterNotebook
                    </a>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="2.3.1" data-path="python数据分析环境和工具/5.1Jupyter-notebook拓展应用.html">
            
                
                    <a href="../python数据分析环境和工具/5.1Jupyter-notebook拓展应用.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>2.3.1.</b>
                        
                        Jupyter-notebook拓展应用
                    </a>
            
            
        </li>
    

            </ul>
            
        </li>
    
        <li class="chapter " data-level="2.4" data-path="python数据分析环境和工具/包和环境管理器：conda.html">
            
                
                    <a href="../python数据分析环境和工具/包和环境管理器：conda.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>2.4.</b>
                        
                        包和环境管理器：conda
                    </a>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="2.4.1" data-path="python数据分析环境和工具/pip和Virtualenv.html">
            
                
                    <a href="../python数据分析环境和工具/pip和Virtualenv.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>2.4.1.</b>
                        
                        pip和Virtualenv
                    </a>
            
            
        </li>
    

            </ul>
            
        </li>
    
        <li class="chapter " data-level="2.5" data-path="python数据分析环境和工具/3Markdown.html">
            
                
                    <a href="../python数据分析环境和工具/3Markdown.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>2.5.</b>
                        
                        标记语言：Markdown
                    </a>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="2.5.1" data-path="python数据分析环境和工具/4Markdown语法.html">
            
                
                    <a href="../python数据分析环境和工具/4Markdown语法.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>2.5.1.</b>
                        
                        Markdown语法
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="2.5.2" data-path="python数据分析环境和工具/6Gitbook文档.html">
            
                
                    <a href="../python数据分析环境和工具/6Gitbook文档.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>2.5.2.</b>
                        
                        文档管理工具-Gitbook
                    </a>
            
            
        </li>
    

            </ul>
            
        </li>
    

            </ul>
            
        </li>
    
        <li class="chapter " data-level="3" data-path="数据分析库的初步认识/index.html">
            
                
                    <a href="../数据分析库的初步认识/index.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>3.</b>
                        
                        数据分析库-Pandas
                    </a>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="3.1" data-path="数据分析库的初步认识/Pandas创建.html">
            
                
                    <a href="../数据分析库的初步认识/Pandas创建.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>3.1.</b>
                        
                        pandas
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="3.2" data-path="数据分析库的初步认识/Series创建.html">
            
                
                    <a href="../数据分析库的初步认识/Series创建.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>3.2.</b>
                        
                        Series
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="3.3" data-path="数据分析库的初步认识/DataFrame创建.html">
            
                
                    <a href="../数据分析库的初步认识/DataFrame创建.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>3.3.</b>
                        
                        DataFrame对象-创建
                    </a>
            
            
        </li>
    

            </ul>
            
        </li>
    
        <li class="chapter " data-level="4" >
            
            <span><b>4.</b> 数据分析库的操作</span>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="4.1" data-path="数据分析库的操作/1DataFrame查询1-整体.html">
            
                
                    <a href="../数据分析库的操作/1DataFrame查询1-整体.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.1.</b>
                        
                        DataFrame查询1-整体
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="4.2" data-path="数据分析库的操作/2DataFrame查询2-专用查询.html">
            
                
                    <a href="../数据分析库的操作/2DataFrame查询2-专用查询.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.2.</b>
                        
                        DataFrame查询2-专用查询
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="4.3" data-path="数据分析库的操作/3DataFrame查询3-专有查询：过滤查询.html">
            
                
                    <a href="../数据分析库的操作/3DataFrame查询3-专有查询：过滤查询.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.3.</b>
                        
                        DataFrame查询3-专有查询：过滤查询
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="4.4" data-path="数据分析库的操作/4Pandas对象的数据操作：增删改查.html">
            
                
                    <a href="../数据分析库的操作/4Pandas对象的数据操作：增删改查.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.4.</b>
                        
                        Pandas对象的数据操作：增删改查
                    </a>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="4.4.1" data-path="数据分析库的操作/5Pandas数据操作：其他操作.html">
            
                
                    <a href="../数据分析库的操作/5Pandas数据操作：其他操作.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.4.1.</b>
                        
                        Pandas数据操作：其他操作
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="4.4.2" data-path="数据分析库的操作/6Pandas数据存取.html">
            
                
                    <a href="../数据分析库的操作/6Pandas数据存取.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.4.2.</b>
                        
                        Pandas数据存取
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="4.4.3" data-path="数据分析库的操作/7Pandas数据运算.html">
            
                
                    <a href="../数据分析库的操作/7Pandas数据运算.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.4.3.</b>
                        
                        Pandas数据运算
                    </a>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="4.4.3.1" data-path="数据分析库的操作/7.1Pandas数据运算拓展.html">
            
                
                    <a href="../数据分析库的操作/7.1Pandas数据运算拓展.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.4.3.1.</b>
                        
                        Pandas数据运算-拓展
                    </a>
            
            
        </li>
    

            </ul>
            
        </li>
    
        <li class="chapter " data-level="4.4.4" data-path="数据分析库的操作/8Pandas分组聚合1.html">
            
                
                    <a href="../数据分析库的操作/8Pandas分组聚合1.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.4.4.</b>
                        
                        Pandas分组聚合1
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="4.4.5" data-path="数据分析库的操作/9Pandas分组聚合2.html">
            
                
                    <a href="../数据分析库的操作/9Pandas分组聚合2.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.4.5.</b>
                        
                        Pandas分组聚合2
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="4.4.6" data-path="数据分析库的操作/10Pandas数据规整-清理.html">
            
                
                    <a href="../数据分析库的操作/10Pandas数据规整-清理.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.4.6.</b>
                        
                        Pandas数据规整-清理
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="4.4.7" data-path="数据分析库的操作/11Pandas数据规整-转换.html">
            
                
                    <a href="../数据分析库的操作/11Pandas数据规整-转换.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.4.7.</b>
                        
                        Pandas数据规整-转换
                    </a>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="4.4.7.1" data-path="数据分析库的操作/14Pandas数据规整-转换-离散化和面元划分.html">
            
                
                    <a href="../数据分析库的操作/14Pandas数据规整-转换-离散化和面元划分.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.4.7.1.</b>
                        
                        离散化和面元划分
                    </a>
            
            
        </li>
    

            </ul>
            
        </li>
    
        <li class="chapter " data-level="4.4.8" data-path="数据分析库的操作/16Pandas数据规整-合并.html">
            
                
                    <a href="../数据分析库的操作/16Pandas数据规整-合并.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.4.8.</b>
                        
                        Pandas数据规整-合并
                    </a>
            
            
        </li>
    

            </ul>
            
        </li>
    
        <li class="chapter " data-level="4.5" data-path="数据分析库的操作/13Pandas数据规整-重塑和轴向旋转.html">
            
                
                    <a href="../数据分析库的操作/13Pandas数据规整-重塑和轴向旋转.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.5.</b>
                        
                        Pandas数据规整-重塑和轴向旋转
                    </a>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="4.5.1" data-path="数据分析库的操作/13.1透视表和交叉表.html">
            
                
                    <a href="../数据分析库的操作/13.1透视表和交叉表.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>4.5.1.</b>
                        
                        透视表和交叉表
                    </a>
            
            
        </li>
    

            </ul>
            
        </li>
    

            </ul>
            
        </li>
    
        <li class="chapter active" data-level="5" data-path="Python可视化/绘图库-Matplotlib.html">
            
                
                    <a href="../Python可视化/绘图库-Matplotlib.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>5.</b>
                        
                        Python可视化
                    </a>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="5.1" data-path="Python可视化/绘图库-Matplotlib/Matplotlib常见图表.html">
            
                
                    <a href="../Python可视化/绘图库-Matplotlib/Matplotlib常见图表.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>5.1.</b>
                        
                        基础：Matplotlib常见图表
                    </a>
            
            
            <ul class="articles">
                
    
        <li class="chapter " data-level="5.1.1" data-path="Python可视化/绘图库-Matplotlib/Matplotlib常见设置和操作.html">
            
                
                    <a href="../Python可视化/绘图库-Matplotlib/Matplotlib常见设置和操作.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>5.1.1.</b>
                        
                        Matplotlib常见设置和操作
                    </a>
            
            
        </li>
    

            </ul>
            
        </li>
    
        <li class="chapter " data-level="5.2" data-path="Python可视化/绘图库-Matplotlib/1Matplotlib-绘图区域.html">
            
                
                    <a href="../Python可视化/绘图库-Matplotlib/1Matplotlib-绘图区域.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>5.2.</b>
                        
                        提升：绘图区域
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="5.3" data-path="Python可视化/绘图库-Matplotlib/2Matplotlib-图像组件.html">
            
                
                    <a href="../Python可视化/绘图库-Matplotlib/2Matplotlib-图像组件.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>5.3.</b>
                        
                        提升：绘图组件
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="5.4" data-path="Python可视化/绘图库-Matplotlib/3Matplotlib-高级绘图.html">
            
                
                    <a href="../Python可视化/绘图库-Matplotlib/3Matplotlib-高级绘图.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>5.4.</b>
                        
                        拓展：高级绘图
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="5.5" data-path="Python可视化/绘图库-Matplotlib/4数学计算展示图像.html">
            
                
                    <a href="../Python可视化/绘图库-Matplotlib/4数学计算展示图像.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>5.5.</b>
                        
                        拓展：数学计算展示图像
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="5.6" data-path="Python可视化/绘图库-Matplotlib/5注意事项.html">
            
                
                    <a href="../Python可视化/绘图库-Matplotlib/5注意事项.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>5.6.</b>
                        
                        拓展：注意事项
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="5.7" data-path="Python可视化/绘图库-Matplotlib/6pylab.html">
            
                
                    <a href="../Python可视化/绘图库-Matplotlib/6pylab.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>5.7.</b>
                        
                        拓展：pylab
                    </a>
            
            
        </li>
    

            </ul>
            
        </li>
    
        <li class="chapter " data-level="6" data-path="数据分析必备知识点/数据分析必备知识点汇集.html">
            
                
                    <a href="../数据分析必备知识点/数据分析必备知识点汇集.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>6.</b>
                        
                        数据分析必备知识点
                    </a>
            
            
        </li>
    
        <li class="chapter " data-level="7" data-path="数据分析必备知识点/数据分析流程.html">
            
                
                    <a href="../数据分析必备知识点/数据分析流程.html">
                
                        <i class="fa fa-check"></i>
                        
                            <b>7.</b>
                        
                        数据分析流程
                    </a>
            
            
        </li>
    


            
            <li class="divider"></li>
            <li>
                <a href="https://www.gitbook.com" target="blank" class="gitbook-link">
                    Published with GitBook
                </a>
            </li>
            
        </ul>
    </nav>
</div>

    <div class="book-body">
        <div class="body-inner">
            <div class="book-header" role="navigation">
    <!-- Actions Left -->
    

    <!-- Title -->
    <h1>
        <i class="fa fa-circle-o-notch fa-spin"></i>
        <a href="../" >Python 数据分析学习目录</a>
    </h1>
</div>

            <div class="page-wrapper" tabindex="-1" role="main">
                <div class="page-inner">
                
                
                    <section class="normal" id="section-">
                    
                        <hr>
<h1 id="&#x7ED8;&#x56FE;&#x5E93;matplotlib">&#x7ED8;&#x56FE;&#x5E93;-Matplotlib</h1>
<h3 id="&#x4E3A;&#x4EC0;&#x4E48;&#x8981;&#x7ED8;&#x56FE;&#xFF1F;">&#x4E3A;&#x4EC0;&#x4E48;&#x8981;&#x7ED8;&#x56FE;&#xFF1F;</h3>
<h4 id="&#x4E00;&#x4E2A;&#x56FE;&#x8868;&#x6570;&#x636E;&#x7684;&#x76F4;&#x89C2;&#x5206;&#x6790;&#xFF1A;">&#x4E00;&#x4E2A;&#x56FE;&#x8868;&#x6570;&#x636E;&#x7684;&#x76F4;&#x89C2;&#x5206;&#x6790;&#xFF1A;</h4>
<p>&#x53EF;&#x89C6;&#x5316;&#x524D;</p>
<p>&#x53EF;&#x89C6;&#x5316;&#x540E;</p>
<p>&#x7ED8;&#x5236;&#x4E4B;&#x524D;&#x5148;&#x91CD;&#x542F;&#x7F16;&#x8F91;&#x5668;&#xFF0C;&#x6E05;&#x9664;&#x4E4B;&#x524D;&#x6267;&#x884C;&#x7684;&#x4EE3;&#x7801;&#x7ED3;&#x679C;</p>
<p><img src="images/matplotlib.svg" alt="png"></p>
<ul>
<li>Matplotlib&#x662F;&#x6700;&#x6D41;&#x884C;&#x7684;Python&#x4E8C;&#x7EF4;&#x5E95;&#x5C42;&#x7ED8;&#x56FE;&#x5E93;&#xFF0C;&#x4E3B;&#x8981;&#x7528;&#x505A;&#x6570;&#x636E;&#x53EF;&#x89C6;&#x5316;&#x56FE;&#x8868;&#x7ED8;&#x5236;</li>
<li>&#x540D;&#x5B57;&#x53D6;&#x6750;&#x4E8E;MATLAB&#xFF0C;&#x6A21;&#x4EFF;MATLAB&#x6784;&#x5EFA;</li>
<li>&#x652F;&#x6301;&#x6240;&#x6709;2D&#x4F5C;&#x56FE;&#x548C;&#x90E8;&#x5206;3D&#x4F5C;&#x56FE;</li>
<li>&#x751F;&#x6210;&#x5370;&#x5237;&#x8D28;&#x91CF;&#x56FE;&#x50CF;</li>
<li>&#x5B98;&#x65B9;&#x7ED8;&#x56FE;&#x793A;&#x4F8B;&#x5C55;&#x793A;&#xFF1A;<a href="http://matplotlib.org/gallery.html" target="_blank">http://matplotlib.org/gallery.html</a><ul>
<li>&#x672C;&#x5730;&#x7248;&#xFF1A;Matplotlib&#x56FE;&#x4F8B;</li>
</ul>
</li>
</ul>
<h2 id="&#x7ED8;&#x5236;&#x6211;&#x7684;&#x7B2C;&#x4E00;&#x4E2A;&#x56FE;&#x8868;">&#x7ED8;&#x5236;&#x6211;&#x7684;&#x7B2C;&#x4E00;&#x4E2A;&#x56FE;&#x8868;</h2>
<pre><code class="lang-python"><span class="hljs-comment"># &#x8F7D;&#x5165;Matplotlib&#x7684;pyplot&#x5B50;&#x5E93;</span>
<span class="hljs-keyword">import</span> matplotlib.pyplot <span class="hljs-keyword">as</span> plt
</code></pre>
<pre><code class="lang-python">plt.plot(
    [<span class="hljs-number">0</span>,<span class="hljs-number">2</span>,<span class="hljs-number">4</span>,<span class="hljs-number">6</span>,<span class="hljs-number">8</span>],  <span class="hljs-comment"># X&#x8F74;&#x5750;&#x6807;&#x503C;</span>
    [<span class="hljs-number">1</span>,<span class="hljs-number">5</span>,<span class="hljs-number">3</span>,<span class="hljs-number">9</span>,<span class="hljs-number">7</span>],  <span class="hljs-comment"># Y&#x8F74;&#x5750;&#x6807;&#x503C;</span>
) 

plt.show()  <span class="hljs-comment"># &#x663E;&#x793A;&#x56FE;&#x50CF;</span>
</code></pre>
<p><img src="images/output_3_0.png" alt="png"></p>
<p>&#x6570;&#x636E;</p>
<pre><code class="lang-python">x = [<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>,<span class="hljs-number">4</span>,<span class="hljs-number">5</span>,<span class="hljs-number">6</span>,<span class="hljs-number">7</span>]
y = [<span class="hljs-number">2</span>,<span class="hljs-number">9</span>,<span class="hljs-number">4</span>,<span class="hljs-number">7</span>,<span class="hljs-number">3</span>,<span class="hljs-number">6</span>,<span class="hljs-number">23</span>]
x,y
</code></pre>
<pre><code>([1, 2, 3, 4, 5, 6, 7], [2, 9, 4, 7, 3, 6, 23])
</code></pre><p>&#x7ED8;&#x56FE;</p>
<pre><code class="lang-python">plt.plot(x,y)
</code></pre>
<pre><code>[&lt;matplotlib.lines.Line2D at 0x7a15748&gt;]
</code></pre><p><img src="images/output_7_1.png" alt="png"></p>
<pre><code class="lang-python"><span class="hljs-comment"># &#x65E7;&#x7248;&#x7684;Ipython &#x7ED8;&#x56FE;&#x540E;&#x9700;&#x8981;&#x624B;&#x52A8;&#x663E;&#x793A;&#x56FE;&#x50CF;</span>
plt.plot(x,y)
plt.show()   <span class="hljs-comment">#&#x663E;&#x793A;&#x56FE;&#x50CF;</span>
</code></pre>
<p><img src="images/output_8_0.png" alt="png"></p>
<p>&#x7ED8;&#x56FE;&#x4F53;&#x9A8C;</p>
<pre><code class="lang-python"><span class="hljs-string">&quot;&quot;&quot;
==========================
Rotating 3D wireframe plot
==========================

A very simple &apos;animation&apos; of a 3D plot.  See also rotate_axes3d_demo.
&quot;&quot;&quot;</span>

<span class="hljs-keyword">from</span> __future__ <span class="hljs-keyword">import</span> print_function

<span class="hljs-keyword">from</span> mpl_toolkits.mplot3d <span class="hljs-keyword">import</span> axes3d
<span class="hljs-keyword">import</span> matplotlib.pyplot <span class="hljs-keyword">as</span> plt
<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
<span class="hljs-keyword">import</span> time
</code></pre>
<pre><code class="lang-python">%matplotlib qt5
</code></pre>
<pre><code class="lang-python">
<span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">generate</span><span class="hljs-params">(X, Y, phi)</span>:</span>
    <span class="hljs-string">&apos;&apos;&apos;
    Generates Z data for the points in the X, Y meshgrid and parameter phi.
    &apos;&apos;&apos;</span>
    R = <span class="hljs-number">1</span> - np.sqrt(X**<span class="hljs-number">2</span> + Y**<span class="hljs-number">2</span>)
    <span class="hljs-keyword">return</span> np.cos(<span class="hljs-number">2</span> * np.pi * X + phi) * R


fig = plt.figure()
ax = fig.add_subplot(<span class="hljs-number">111</span>, projection=<span class="hljs-string">&apos;3d&apos;</span>)

<span class="hljs-comment"># Make the X, Y meshgrid.</span>
xs = np.linspace(-<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">50</span>)
ys = np.linspace(-<span class="hljs-number">1</span>, <span class="hljs-number">1</span>, <span class="hljs-number">50</span>)
X, Y = np.meshgrid(xs, ys)

<span class="hljs-comment"># Set the z axis limits so they aren&apos;t recalculated each frame.</span>
ax.set_zlim(-<span class="hljs-number">1</span>, <span class="hljs-number">1</span>)

<span class="hljs-comment"># Begin plotting.</span>
wframe = <span class="hljs-keyword">None</span>
tstart = time.time()
<span class="hljs-keyword">for</span> phi <span class="hljs-keyword">in</span> np.linspace(<span class="hljs-number">0</span>, <span class="hljs-number">180.</span> / np.pi, <span class="hljs-number">100</span>):
    <span class="hljs-comment"># If a line collection is already remove it before drawing.</span>
    <span class="hljs-keyword">if</span> wframe:
        ax.collections.remove(wframe)

    <span class="hljs-comment"># Plot the new wireframe and pause briefly before continuing.</span>
    Z = generate(X, Y, phi)
    wframe = ax.plot_wireframe(X, Y, Z, rstride=<span class="hljs-number">2</span>, cstride=<span class="hljs-number">2</span>)
    plt.pause(<span class="hljs-number">.001</span>)

print(<span class="hljs-string">&apos;Average FPS: %f&apos;</span> % (<span class="hljs-number">100</span> / (time.time() - tstart)))
</code></pre>
<p><img src="images/Figure_1.png" alt="png"></p>
<pre><code>Average FPS: 26.295642
</code></pre><pre><code class="lang-python"><span class="hljs-string">&quot;&quot;&quot;
.. versionadded:: 1.1.0
   This demo depends on new features added to contourf3d.
&quot;&quot;&quot;</span>

<span class="hljs-keyword">from</span> mpl_toolkits.mplot3d <span class="hljs-keyword">import</span> axes3d
<span class="hljs-keyword">import</span> matplotlib.pyplot <span class="hljs-keyword">as</span> plt
<span class="hljs-keyword">from</span> matplotlib <span class="hljs-keyword">import</span> cm
</code></pre>
<pre><code class="lang-python">fig = plt.figure()
ax = fig.gca(projection=<span class="hljs-string">&apos;3d&apos;</span>)
X, Y, Z = axes3d.get_test_data(<span class="hljs-number">0.05</span>)
ax.plot_surface(X, Y, Z, rstride=<span class="hljs-number">8</span>, cstride=<span class="hljs-number">8</span>, alpha=<span class="hljs-number">0.3</span>)
cset = ax.contourf(X, Y, Z, zdir=<span class="hljs-string">&apos;z&apos;</span>, offset=-<span class="hljs-number">100</span>, cmap=cm.coolwarm)
cset = ax.contourf(X, Y, Z, zdir=<span class="hljs-string">&apos;x&apos;</span>, offset=-<span class="hljs-number">40</span>, cmap=cm.coolwarm)
cset = ax.contourf(X, Y, Z, zdir=<span class="hljs-string">&apos;y&apos;</span>, offset=<span class="hljs-number">40</span>, cmap=cm.coolwarm)

ax.set_xlabel(<span class="hljs-string">&apos;X&apos;</span>)
ax.set_xlim(-<span class="hljs-number">40</span>, <span class="hljs-number">40</span>)
ax.set_ylabel(<span class="hljs-string">&apos;Y&apos;</span>)
ax.set_ylim(-<span class="hljs-number">40</span>, <span class="hljs-number">40</span>)
ax.set_zlabel(<span class="hljs-string">&apos;Z&apos;</span>)
ax.set_zlim(-<span class="hljs-number">100</span>, <span class="hljs-number">100</span>)

plt.show()
</code></pre>
<p><img src="images/output_14_0.png" alt="png"></p>
<pre><code class="lang-python"><span class="hljs-comment"># Plot of the Lorenz Attractor based on Edward Lorenz&apos;s 1963 &quot;Deterministic</span>
<span class="hljs-comment"># Nonperiodic Flow&quot; publication.</span>
<span class="hljs-comment"># http://journals.ametsoc.org/doi/abs/10.1175/1520-0469%281963%29020%3C0130%3ADNF%3E2.0.CO%3B2</span>
<span class="hljs-comment">#</span>
<span class="hljs-comment"># Note: Because this is a simple non-linear ODE, it would be more easily</span>
<span class="hljs-comment">#       done using SciPy&apos;s ode solver, but this approach depends only</span>
<span class="hljs-comment">#       upon NumPy.</span>

<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
<span class="hljs-keyword">import</span> matplotlib.pyplot <span class="hljs-keyword">as</span> plt
<span class="hljs-keyword">from</span> mpl_toolkits.mplot3d <span class="hljs-keyword">import</span> Axes3D
</code></pre>
<pre><code class="lang-python"><span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">lorenz</span><span class="hljs-params">(x, y, z, s=<span class="hljs-number">10</span>, r=<span class="hljs-number">28</span>, b=<span class="hljs-number">2.667</span>)</span>:</span>
    x_dot = s*(y - x)
    y_dot = r*x - y - x*z
    z_dot = x*y - b*z
    <span class="hljs-keyword">return</span> x_dot, y_dot, z_dot


dt = <span class="hljs-number">0.01</span>
stepCnt = <span class="hljs-number">10000</span>

<span class="hljs-comment"># Need one more for the initial values</span>
xs = np.empty((stepCnt + <span class="hljs-number">1</span>,))
ys = np.empty((stepCnt + <span class="hljs-number">1</span>,))
zs = np.empty((stepCnt + <span class="hljs-number">1</span>,))

<span class="hljs-comment"># Setting initial values</span>
xs[<span class="hljs-number">0</span>], ys[<span class="hljs-number">0</span>], zs[<span class="hljs-number">0</span>] = (<span class="hljs-number">0.</span>, <span class="hljs-number">1.</span>, <span class="hljs-number">1.05</span>)

<span class="hljs-comment"># Stepping through &quot;time&quot;.</span>
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> range(stepCnt):
    <span class="hljs-comment"># Derivatives of the X, Y, Z state</span>
    x_dot, y_dot, z_dot = lorenz(xs[i], ys[i], zs[i])
    xs[i + <span class="hljs-number">1</span>] = xs[i] + (x_dot * dt)
    ys[i + <span class="hljs-number">1</span>] = ys[i] + (y_dot * dt)
    zs[i + <span class="hljs-number">1</span>] = zs[i] + (z_dot * dt)

fig = plt.figure()
ax = fig.gca(projection=<span class="hljs-string">&apos;3d&apos;</span>)

ax.plot(xs, ys, zs, lw=<span class="hljs-number">0.5</span>)
ax.set_xlabel(<span class="hljs-string">&quot;X Axis&quot;</span>)
ax.set_ylabel(<span class="hljs-string">&quot;Y Axis&quot;</span>)
ax.set_zlabel(<span class="hljs-string">&quot;Z Axis&quot;</span>)
ax.set_title(<span class="hljs-string">&quot;Lorenz Attractor&quot;</span>)

plt.show()
</code></pre>
<p><img src="images/output_16_0.png" alt="png"></p>

                    
                    </section>
                
                
                </div>
            </div>
        </div>

        
        <a href="../数据分析库的操作/13.1透视表和交叉表.html" class="navigation navigation-prev " aria-label="Previous page: 透视表和交叉表"><i class="fa fa-angle-left"></i></a>
        
        
        <a href="../Python可视化/绘图库-Matplotlib/Matplotlib常见图表.html" class="navigation navigation-next " aria-label="Next page: 基础：Matplotlib常见图表"><i class="fa fa-angle-right"></i></a>
        
    </div>
</div>

        
<script src="../gitbook/app.js"></script>

    
    <script src="../gitbook/plugins/gitbook-plugin-search/lunr.min.js"></script>
    

    
    <script src="../gitbook/plugins/gitbook-plugin-search/search.js"></script>
    

    
    <script src="../gitbook/plugins/gitbook-plugin-sharing/buttons.js"></script>
    

    
    <script src="../gitbook/plugins/gitbook-plugin-fontsettings/buttons.js"></script>
    

<script>
require(["gitbook"], function(gitbook) {
    var config = {"highlight":{},"search":{"maxIndexSize":1000000},"sharing":{"facebook":true,"twitter":true,"google":false,"weibo":false,"instapaper":false,"vk":false,"all":["facebook","google","twitter","weibo","instapaper"]},"fontsettings":{"theme":"white","family":"sans","size":2}};
    gitbook.start(config);
});
</script>

        
    </body>
    
</html>
